Dashboard

library(tidyverse)

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library(p8105.datasets)
library(dplyr)
library(tidyr)
library(plotly)

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library(ggridges)
library(httr)

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library(jsonlite)

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library(flexdashboard)

Column

Chart A

data("instacart")

instacart_department =
  count(instacart, department) %>% 
  arrange(n) %>% 
  mutate(
    department = factor(department, levels = department)
  )

instacart_department %>% 
  plot_ly(x = ~n, y = ~department, color = ~department, type = "bar", colors = "viridis")

Column

Chart B

instacart_aisle = count(instacart, aisle) %>% 
  filter(n > 10000) %>% 
  arrange(n) %>% 
  mutate(
    aisle = factor(aisle, levels = aisle)
  )

instacart_aisle %>% 
  plot_ly(x = ~n, y = ~aisle, color = ~aisle, alpha = .5,
    type = "scatter", mode = "markers"
  )

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

Chart C

data("instacart")

instacart_3 = instacart %>% 
  filter( days_since_prior_order <= 10) %>%
  mutate(department = str_to_title(department)) %>% 
  mutate(
    department = fct_infreq(department),
    department = fct_recode(department)) %>% 
  select(department, order_number)
  


instacart_3 %>% 
  plot_ly(
      x = ~department, y = ~order_number, color = ~department,
      type = "box", colors = "viridis"
    )

# instacart_3 = instacart %>% 
#   filter( aisle == "baking ingredients" | aisle == "dog food care" | aisle == "packaged vegetables fruits") %>% 
#   select(aisle, department, order_number)
# 
# 
# instacart_3 %>% 
#   plot_ly(
#       x = ~aisle, y = ~order_number, color = ~department,
#       type = "box", colors = "viridis"
#     )